Deep learning is a recent development in computer science, based on
creating computational models that feature multiple layers and
correspondingly increasingly higher levels of abstraction. We use the
problem of distinguishing hadronic top quark decays from light quark and
gluon jets (top tagging) as a starting point for a tour of deep learning
techniques in particle physics and their prospects for the future.